@inproceedings{6361e4d1f01f449aa6648d1f4429aff9,
title = "Image reconstruction and compressive sensing in MIMO radar",
abstract = "Multiple-input multiple-output (MIMO) radar utilizes the flexible configuration of transmitting and receiving antennas to construct images of target scenes. Because of the target scenes' sparsity, the compressive sensing (CS) technique can be used to realize a feasible reconstruction of the target scenes from undersampling data. This paper presents the signal model of MIMO radar and derive the corresponding CS measurement matrix, which shows success of the CS technique. Also the basis pursuit method and total-variation minimization method are adopted for different scenes' recovery. Numerical simulations are provided to illustrate the validity of reconstruction for one dimensional and two dimensional scenes.",
keywords = "Multiple-input multiple-output, basis pursuit, compressive sensing, total-variation minimization",
author = "Bing Sun and Juan Lopez and Zhijun Qiao",
year = "2014",
doi = "10.1117/12.2051275",
language = "英语",
isbn = "9781628410143",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
booktitle = "Radar Sensor Technology XVIII",
address = "美国",
note = "Radar Sensor Technology XVIII ; Conference date: 05-05-2014 Through 07-05-2014",
}